Assessment of the impact in climate index anomaly on maize yield in Northeast China based on the boosted regression tree

Northeast China is one of the major maize-producing regions in China, playing a pivotal role in national food security. Maize is highly sensitive to inter-annual variations in both average and extreme climatic conditions. Identifying the key climatic variables affecting maize yield is crucial for maize production management. In this study, a fundamental database is constructed, integrating maize phenology data, yield data, and meteorological records from agro-meteorological observation stations across the three provinces of Northeast China (Heilongjiang, Jilin, and Liaoning) spanning the period 1981–2022. The boosted regression tree (BRT) model is employed to quantify the impacts of anomalies in average climatic indicators, extreme temperature indicators, and temperature-moisture compound indicators on the meteorological yield of spring maize during maize different growing periods. The results show that the meteorological yield of spring maize in the three provinces exhibit significant inter-annual fluctuations, with distinct variations across different decades. The BRT model effectively disentangle the primary factors driving regional maize yield changes, with cross-validation coefficients ranging from 0.61 to 0.75. Based on the BRT models of different periods, the dominant factors influencing spring maize meteorological yield vary across decades: During the period from 1981 to 1990, anomalies in relative humidity (average precipitation) are the primary factor affecting regional maize yield; During the period from 1991 to 2000, anomalies in heat growing degree days (extreme high temperatures) during the maize growing season become the dominant factor; During the periods from 2001 to 2010 and from 2011 to 2022, anomalies in heat growing degree days (extreme high temperatures) during the reproductive growing stage of maize emerge as the key driver of maize yield. Notably, the contribution of anomalies in extreme low temperatures during the reproductive growing stage to spring maize yield in the study region gradually increase over the decades. Specifically: During the periods from 1991 to 2000 and from 2001 to 2010, anomalies in cold growing degree days during the reproductive growing stage of spring maize exert a negative effect on maize yield; In contrast, during the period from 2011 to 2022, these anomalies shift to a positive effect on maize yield. Overall, anomalies in heat growing degree days are the dominant factor influencing maize meteorological yield. Furthermore, as the anomaly in cold growing degree days shows a decreasing trend, the impact of extreme low-temperature anomalies on maize yield in Northeast China gradually transitions from a negative to a positive effect. In the future, it is essential to make full use of the reduction in extreme low-temperature stress and minimize the harm caused by extreme high temperatures to ensure high and stable maize yields in Northeast China.